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Balsa: Learning a Query Optimizer Without Expert Demonstrations

Summary: Balsa uses deep RL to learn a query optimizer without expert demonstrations, from a simple simulator to safe real-execution fine-tuning. On Join Order Benchmark, it matches two expert optimizers after ~2 hours and beats them up to 2.8x with training. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
hc15b634968a29395
Venue
SIGMOD
Year
2022
Pagerank
0.00011563985
Overall Rank
1,199 | 91.95%
DOI
10.1145/3514221.3517885

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{yang_sigmod22,
        title = {{Balsa: Learning a Query Optimizer Without Expert Demonstrations}},
        author = {Yang, Zongheng and Chiang, Wei-Lin and Luan, Sifei and Mittal, Gautam and Luo, Michael and Stoica, Ion},
        series = {{SIGMOD} '22},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3514221.3517885},
        url = {https://dl.acm.org/doi/10.1145/3514221.3517885},
        year = {2022}
}

Incoming Citations (Sorted by Pagerank)

Showing 50 of 59 citing papers.

Rank Citing Paper Year Venue Pagerank
2,210 Lero: A Learning-to-Rank Query Optimizer 2023 VLDB 8.8257742e-05
3,487 LOGER: A Learned Optimizer towards Generating Efficient and Robust Query Execution Plans 2023 VLDB 7.263041e-05
3,563 Auto-WLM: Machine Learning Enhanced Workload Management in Amazon Redshift 2023 SIGMOD 7.2042148e-05
4,202 Kepler: Robust Learning for Faster Parametric Query Optimization 2023 SIGMOD 6.7374091e-05
4,258 LEON: A New Framework for ML-Aided Query Optimization 2023 VLDB 6.6994722e-05
4,683 AutoSteer: Learned Query Optimization for Any SQL Database 2023 VLDB 6.4716143e-05
5,214 Stage: Query Execution Time Prediction in Amazon Redshift 2024 SIGMOD 6.2248104e-05
5,241 FASTgres: Making Learned Query Optimizer Hinting Effective 2023 VLDB 6.2154384e-05
5,456 Eraser: Eliminating Performance Regression on Learned Query Optimizer 2024 VLDB 6.1239873e-05
5,649 Sample-Efficient Cardinality Estimation Using Geometric Deep Learning 2024 VLDB 6.052326e-05
5,683 How Good are Learned Cost Models, Really? Insights from Query Optimization Tasks 2025 SIGMOD 6.0392183e-05
5,788 Lemo: A Cache-Enhanced Learned Optimizer for Concurrent Queries 2023 SIGMOD 5.9947442e-05
5,871 PilotScope: Steering Databases with Machine Learning Drivers 2024 VLDB 5.9639223e-05
6,308 Is Your Learned Query Optimizer Behaving As You Expect? A Machine Learning Perspective 2024 VLDB 5.8177833e-05
6,586 Can Large Language Models Be Query Optimizer for Relational Databases? 2026 SIGMOD 5.7430662e-05
6,632 Join Order Selection with Deep Reinforcement Learning: Fundamentals, Techniques, and Challenges 2023 VLDB 5.7270153e-05
6,660 Speeding Up End-to-end Query Execution via Learning-based Progressive Cardinality Estimation 2023 SIGMOD 5.7178404e-05
6,710 Simple Adaptive Query Processing vs. Learned Query Optimizers: Observations and Analysis 2023 VLDB 5.7019157e-05
7,033 Rethinking Learned Cost Models: Why Start from Scratch? 2023 SIGMOD 5.6168499e-05
7,070 E2ETune: End-to-End Knob Tuning via Fine-tuned Generative Language Model 2025 VLDB 5.6080535e-05
7,460 T3: Accurate and Fast Performance Prediction for Relational Database Systems With Compiled Decision Trees 2025 SIGMOD 5.5215755e-05
7,931 SlabCity: Whole-Query Optimization using Program Synthesis 2023 VLDB 5.4238328e-05
7,977 The Holon Approach for Simultaneously Tuning Multiple Components in a Self-Driving Database Management System with Machine Learning via Synthesized Proto-Actions 2024 VLDB 5.4142519e-05
8,332 Learned Offline Query Planning via Bayesian Optimization 2025 SIGMOD 5.3528188e-05
9,133 Hit the Gym: Accelerating Query Execution to Efficiently Bootstrap Behavior Models for Self-Driving Database Management Systems 2024 VLDB 5.2229655e-05
9,276 BASE: Bridging the Gap between Cost and Latency for Query Optimization 2023 VLDB 5.204289e-05
9,300 GenJoin: Conditional Generative Plan-to-Plan Query Optimizer that Learns from Subplan Hints 2026 SIGMOD 5.1987909e-05
9,546 Athena: An Effective Learning-based Framework for Query Optimizer Performance Improvement 2025 SIGMOD 5.1604755e-05
9,610 LIMAO: A Framework for Lifelong Modular Learned Query Optimization 2025 VLDB 5.1526493e-05
9,656 BladeDISC: Optimizing Dynamic Shape Machine Learning Workloads via Compiler Approach 2023 SIGMOD 5.1453267e-05
9,670 Low Rank Learning for Offline Query Optimization 2025 SIGMOD 5.1452097e-05
9,720 APQO: An Adaptive Framework for Parametric Query Optimization 2026 SIGMOD 5.1349531e-05
9,797 NeuSO: Neural Optimizer for Subgraph Queries 2026 SIGMOD 5.1257999e-05
9,893 Approximate Sketches 2024 SIGMOD 5.1134687e-05
9,954 Conformal Prediction for Verifiable Learned Query Optimization 2025 VLDB 5.1038322e-05
9,956 Graph Transformers for Query Plan Representation: Potentials and Challenges 2025 VLDB 5.1038322e-05
10,148 Improving DBMS Scheduling Decisions with Accurate Performance Prediction on Concurrent Queries 2025 VLDB 5.0715586e-05
10,285 Towards Full Stack Adaptivity in Permissioned Blockchains 2024 VLDB 5.0448662e-05
10,310 veDB-HTAP: a Highly Integrated, Efficient and Adaptive HTAP System 2025 VLDB 5.0386264e-05
10,336 An Elephant Under The Microscope: Analyzing The Interaction Of Optimizer Components In PostgreSQL 2025 SIGMOD 5.0200193e-05
10,412 Are Learned DBMS Components Robust to Workload Drift?: [Experiments & Analysis] 2026 SIGMOD 4.9793485e-05
10,484 NeurBench: A Benchmark Suite for Learned Database Components with Drift Modeling: [Experiments & Analysis] 2026 SIGMOD 4.9793485e-05
10,489 On Self-Designing Learned Indexes 2026 SIGMOD 4.9793485e-05
10,508 Succinct Structure Representations for Efficient Query Optimization 2026 SIGMOD 4.9793485e-05
10,532 Rainbow: Risk-aware Index Benefit Estimation Facing Out Of Distribution Workloads 2026 SIGMOD 4.9793485e-05
10,596 SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer 2026 SIGMOD 4.9793485e-05
10,633 Divo: Learning a Stable and Effective Query Optimizer with a Diverse Workload 2026 SIGMOD 4.9793485e-05
10,693 Practical Parameterized Query Optimization via Efficient Plan Reuse and List-wise Ranking 2026 SIGMOD 4.9793485e-05
10,698 LIO: A lightweight and interpretable query optimizer based on an evolutionary forest 2026 VLDB 4.9793485e-05
10,700 Sample-based Distinct Cardinality Estimation for Multiple Attributes in Multi-Dataset Queries 2026 VLDB 4.9793485e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 16 of 16 cited papers.

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